An M-Objective Penalty Function Algorithm Under Big Penalty Parameters

ZHENG Ying,MENG Zhiqing,SHEN Rui

系统科学与复杂性(英文) ›› 2016, Vol. 29 ›› Issue (2) : 455-471.

PDF(219 KB)
PDF(219 KB)
系统科学与复杂性(英文) ›› 2016, Vol. 29 ›› Issue (2) : 455-471. DOI: 10.1007/s11424-015-3204-3

An M-Objective Penalty Function Algorithm Under Big Penalty Parameters

    ZHENG Ying1 , MENG Zhiqing 2, SHEN Rui2
作者信息 +

An M-Objective Penalty Function Algorithm Under Big Penalty Parameters

    ZHENG Ying1 , MENG Zhiqing 2, SHEN Rui2
Author information +
文章历史 +

Abstract

Some classical penalty function algorithms may not always be convergent under big penalty parameters in Matlab software, which makes them impossible to find out an optimal solution to constrained optimization problems. In this paper, a novel penalty function (called M-objective penalty function) with one penalty parameter added to both objective and constrained functions of inequality constrained optimization problems is proposed. Based on the M-objective penalty function, an algorithm is developed to solve an optimal solution to the inequality constrained optimization problems, with its convergence proved under some conditions. Furthermore, numerical results show that the proposed algorithm has a much better convergence than the classical penalty function algorithms under big penalty parameters, and is efficient in choosing a penalty parameter in a large range in Matlab software.

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ZHENG Ying,MENG Zhiqing,SHEN Rui. An M-Objective Penalty Function Algorithm Under Big Penalty Parameters. 系统科学与复杂性(英文), 2016, 29(2): 455-471 https://doi.org/10.1007/s11424-015-3204-3
ZHENG Ying , MENG Zhiqing , SHEN Rui. An M-Objective Penalty Function Algorithm Under Big Penalty Parameters. Journal of Systems Science and Complexity, 2016, 29(2): 455-471 https://doi.org/10.1007/s11424-015-3204-3
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